A super-resolution reconstruction algorithm for surveillance images

In many surveillance video applications, it is of interest to recognize a region of interest (ROI), which often occupies a small portion of a low-resolution, noisy video. This paper proposes an edge-preserving maximum a posteriori (MAP) estimation based super-resolution algorithm using a weighted directional Markov image prior model for a ROI from more than one low-resolution surveillance image. Conjugate gradient (CG) optimization based on standard operations on images is then developed to improve the computational efficiency of the algorithm. The proposed algorithm is tested on different series of surveillance images. The experimental results indicate that the proposed algorithm has considerable effectiveness in terms of both objective measurements and visual evaluation.

[1]  Aggelos K. Katsaggelos,et al.  High-resolution images from low-resolution compressed video , 2003, IEEE Signal Process. Mag..

[2]  A. Murat Tekalp,et al.  High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur , 1992, Proceedings of 1st International Conference on Image Processing.

[3]  Michael Elad,et al.  Superresolution restoration of an image sequence: adaptive filtering approach , 1999, IEEE Trans. Image Process..

[4]  Yücel Altunbasak,et al.  Super-resolution reconstruction of hyperspectral images , 2004, IEEE Transactions on Image Processing.

[5]  Raymond H. Chan,et al.  Wavelet Algorithms for High-Resolution Image Reconstruction , 2002, SIAM J. Sci. Comput..

[6]  Liangpei Zhang,et al.  A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution , 2007, IEEE Transactions on Image Processing.

[7]  Edmund Y. Lam,et al.  A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video , 2007, EURASIP J. Adv. Signal Process..

[8]  Stephen J. Roberts,et al.  Bayesian Image Super-resolution, Continued , 2006, NIPS.

[9]  Michael Elad,et al.  Fast and robust multiframe super resolution , 2004, IEEE Transactions on Image Processing.

[10]  A. Murat Tekalp,et al.  High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  Russell C. Hardie,et al.  High resolution image reconstruction from digital video with global and non-global scene motion , 1997, Proceedings of International Conference on Image Processing.

[12]  Shmuel Peleg,et al.  Super-Resolution from Multiple Images Having Arbitrary Mutual Motion , 2002 .

[13]  Seunghyeon Rhee,et al.  Discrete cosine transform based regularized high-resolution image reconstruction algorithm , 1999 .

[14]  Aggelos K. Katsaggelos,et al.  Reconstruction of a high-resolution image from multiple-degraded misregistered low-resolution images , 1994, Other Conferences.

[15]  Robert L. Stevenson,et al.  Extraction of high-resolution frames from video sequences , 1996, IEEE Trans. Image Process..

[16]  H Stark,et al.  High-resolution image recovery from image-plane arrays, using convex projections. , 1989, Journal of the Optical Society of America. A, Optics and image science.

[17]  Christopher M. Bishop,et al.  Bayesian Image Super-Resolution , 2002, NIPS.

[18]  Nikolas P. Galatsanos,et al.  Stochastic methods for joint registration, restoration, and interpolation of multiple undersampled images , 2006, IEEE Transactions on Image Processing.

[19]  P. Laguna,et al.  Signal Processing , 2002, Yearbook of Medical Informatics.

[20]  Michael Elad,et al.  Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images , 1997, IEEE Trans. Image Process..

[21]  N. K. Bose,et al.  High resolution image formation from low resolution frames using Delaunay triangulation , 2002, IEEE Trans. Image Process..

[22]  S. Chaudhuri.  Super-Resolution Imaging , 2001 .

[23]  Russell C. Hardie,et al.  Joint MAP registration and high-resolution image estimation using a sequence of undersampled images , 1997, IEEE Trans. Image Process..

[24]  Nirmal K. Bose,et al.  Recursive reconstruction of high resolution image from noisy undersampled multiframes , 1990, IEEE Trans. Acoust. Speech Signal Process..

[25]  A. Murat Tekalp,et al.  Super resolution recovery for multi-camera surveillance imaging , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[26]  Wen-Yu Su,et al.  Recursive high-resolution reconstruction of blurred multiframe images , 1993, IEEE Trans. Image Process..

[27]  Aggelos K. Katsaggelos,et al.  Bayesian resolution enhancement of compressed video , 2004, IEEE Transactions on Image Processing.

[28]  Russell C. Hardie,et al.  High Resolution Image Reconstruction from Digital Video with In-Scene Motion , 1997 .

[29]  Roger Y. Tsai,et al.  Multiframe image restoration and registration , 1984 .

[30]  J. Nagy,et al.  Numerical methods for coupled super-resolution , 2006 .

[31]  Michael Elad,et al.  Multiframe demosaicing and super-resolution of color images , 2006, IEEE Transactions on Image Processing.

[32]  Li Chen,et al.  A soft MAP framework for blind super-resolution image reconstruction , 2009, Image Vis. Comput..

[33]  Michael K. Ng,et al.  Wavelet algorithms for deblurring models , 2004, Int. J. Imaging Syst. Technol..

[34]  Isao Yamada,et al.  A color super-resolution with multiple nonsmooth constraints by hybrid steepest descent method , 2005, IEEE International Conference on Image Processing 2005.

[35]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[36]  Daniel Gross,et al.  Improved resolution from subpixel shifted pictures , 1992, CVGIP Graph. Model. Image Process..

[37]  Andrew J. Patti,et al.  Super Resolution Video Reconstruction with Arbitrary Sampling Lattices and Non-zero Aperture Time , 1997 .

[38]  A. Murat Tekalp,et al.  Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time , 1997, IEEE Trans. Image Process..

[39]  Michal Irani,et al.  Improving resolution by image registration , 1991, CVGIP Graph. Model. Image Process..